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数据准备和特征工程:数据工程师必知必会技能

数据准备和特征工程:数据工程师必知必会技能

1星价 ¥32.4 (7.2折)
2星价¥32.4 定价¥45.0
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  • ISBN:9787121382635
  • 装帧:平装-胶订
  • 册数:暂无
  • 重量:暂无
  • 开本:26cm
  • 页数:198页
  • 出版时间:2020-03-01
  • 条形码:9787121382635 ; 978-7-121-38263-5

本书特色

画龙点睛的批注,让学习更加简单案例式教学,面向工程实践渗透技术发展,基础与前沿结合提供在线实验平台,学练融合在专属公众号与作者交互,教学相长配套视频和在线课程,边看边学

内容简介

本书详细地介绍了大数据、人工智能等项目中不可或缺的环节和内容:数据准备和特征工程。书中的每节首先以简明方式介绍了基本知识;然后通过实际案例演示了基本知识的实际应用,并提供了针对性练习项目,将“知识、案例、练习”融为一体;*后以“扩展探究”方式引导读者进入更深广的领域。本书既适合作为大学相关专业的教材,也适合作为大数据、人工智能等领域的开发人员的参考读物。

目录

目录 第1 章 感知数据 ·································.001 1.0 了解数据科学项目 ································001 1.1 文件中的数据 ··································003 1.1.1 CSV文件 ····································003 1.1.2 Excel文件 ···································009 1.1.3 图像文件 ···································015 1.2 数据库中的数据 ·································019 1.3 网页上的数据 ··································029 1.4 来自API 的数据 ·································039 第2 章 数据清理 ··································044 2.0 基本概念 ····································045 2.1 转化数据类型 ··································046 2.2 处理重复数据 ··································054 2.3 处理缺失数据 ··································057 2.3.1 检查缺失数据 ·································058 2.3.2 用指定值填补 ·································063 2.3.3 根据规律填补 ·································069 2.4 处理离群数据 ··································076 第3 章 特征变换 ···································083 3.0 特征的类型 ···································084 3.1 特征数值化 ···································085 3.2 特征二值化 ···································088 3.3 OneHot编码 ···································093 3.4 数据变换 ····································098 3.5 特征离散化 ···································104 3.5.1 无监督离散化 ·································104 3.5.2 有监督离散化 ·································110 3.6 数据规范化 ···································113 第4 章 特征选择 ···································124 4.0 特征选择简述 ··································124 4.1 封装器法 ····································127 4.1.1 循序特征选择 ·································127 4.1.2 穷举特征选择 ·································135 4.1.3 递归特征消除 ·································140 4.2 过滤器法 ····································144 4.3 嵌入法 ·····································149 第5 章 特征抽取 ···································154 5.1 无监督特征抽取··································154 5.1.1 主成分分析 ··································154 5.1.2 因子分析 ···································161 5.2 有监督特征抽取 ·································167 附录A Jupyter简介 ·································173 附录B NumPy简介 ··································176 附录C Pandas简介 ··································185 附录D Matplotlib简介 ································194 后记 ········································199
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作者简介

齐伟,自称老齐,现居苏州,所著在线教程《零基础学Python》及《零基础学Python(第2版)》在业内引起非常大的反响。愿意和来自各方的朋友讨论技术问题,并能提供相关技术服务。

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